Update process_interview.py

process_interview.py

@@ -788,81 +788,81 @@ def create_company_pdf_report(analysis_data: Dict, output_path: str, gemini_repo
             canvas.drawRightString(doc.width + doc.leftMargin, doc.height + 0.95*inch, time.strftime('%B %d, %Y'))
             canvas.restoreState()
 
-            # Title Page
-            story.append(Paragraph("Candidate Interview Analysis", h1))
-            story.append(Paragraph(f"Generated {time.strftime('%B %d, %Y')}", ParagraphStyle(name='Date', alignment=1, fontSize=8, textColor=colors.HexColor('#666666'), fontName='Helvetica')))
-            story.append(Spacer(1, 0.3*inch))
-            acceptance_prob = analysis_data.get('acceptance_probability', 50.0)
-            story.append(Paragraph("Hiring Suitability Snapshot", h2))
-            prob_color = colors.HexColor('#2E7D32') if acceptance_prob >= 80 else colors.HexColor('#F57C00') if acceptance_prob >= 60 else colors.HexColor('#D32F2F')
-            story.append(Paragraph(f"Suitability Score: <font size=14 color='{prob_color.hexval()}'><b>{acceptance_prob:.2f}%</b></font>",
-                                 ParagraphStyle(name='Prob', fontSize=10, spaceAfter=8, alignment=1, fontName='Helvetica-Bold')))
-            if acceptance_prob >= 80:
-                story.append(Paragraph("<b>HR Verdict:</b> Outstanding candidate, recommended for immediate advancement.", body_text))
-            elif acceptance_prob >= 60:
-                story.append(Paragraph("<b>HR Verdict:</b> Strong candidate, suitable for further evaluation.", body_text))
-            elif acceptance_prob >= 40:
-                story.append(Paragraph("<b>HR Verdict:</b> Moderate potential, needs additional assessment.", body_text))
-            else:
-                story.append(Paragraph("<b>HR Verdict:</b> Limited fit, significant improvement required.", body_text))
-            story.append(Spacer(1, 0.2*inch))
-            participants = sorted([p for u in set(u['speaker'] for u in analysis_data['transcript'] if u['speaker'] != ['Unknown'])
-            participants_str = ', '.join(participants)
+        # Title Page
+        story.append(Paragraph("Candidate Interview Analysis", h1))
+        story.append(Paragraph(f"Generated {time.strftime('%B %d, %Y')}", ParagraphStyle(name='Date', alignment=1, fontSize=8, textColor=colors.HexColor('#666666'), fontName='Helvetica')))
+        story.append(Spacer(1, 0.3*inch))
+        acceptance_prob = analysis_data.get('acceptance_probability', 50.0)
+        story.append(Paragraph("Hiring Suitability Snapshot", h2))
+        prob_color = colors.HexColor('#2E7D32') if acceptance_prob >= 80 else colors.HexColor('#F57C00') if acceptance_prob >= 60 else colors.HexColor('#D32F2F')
+        story.append(Paragraph(f"Suitability Score: <font size=14 color='{prob_color.hexval()}'><b>{acceptance_prob:.2f}%</b></font>",
+                               ParagraphStyle(name='Prob', fontSize=10, spaceAfter=8, alignment=1, fontName='Helvetica-Bold')))
+        if acceptance_prob >= 80:
+            story.append(Paragraph("<b>HR Verdict:</b> Outstanding candidate, recommended for immediate advancement.", body_text))
+        elif acceptance_prob >= 60:
+            story.append(Paragraph("<b>HR Verdict:</b> Strong candidate, suitable for further evaluation.", body_text))
+        elif acceptance_prob >= 40:
+            story.append(Paragraph("<b>HR Verdict:</b> Moderate potential, needs additional assessment.", body_text))
+        else:
+            story.append(Paragraph("<b>HR Verdict:</b> Limited fit, significant improvement required.", body_text))
+        story.append(Spacer(1, 0.2*inch))
+        participants = sorted(set(u['speaker'] for u in analysis_data['transcript'] if u['speaker'] != 'Unknown'))
+        participants_str = ', '.join(participants)
+        table_data = [
+            ['Metric', 'Value'],
+            ['Interview Duration', f"{analysis_data['text_analysis']['total_duration']:.2f} seconds"],
+            ['Speaker Turns', f"{analysis_data['text_analysis']['speaker_turns']}"],
+            ['Participants', participants_str],
+        ]
+        table = Table(table_data, colWidths=[2.0*inch, 4.0*inch])
+        table.setStyle(TableStyle([
+            ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#0050BC')),
+            ('TEXTCOLOR', (0,0), (-1,0), colors.white),
+            ('ALIGN', (0,0), (-1,-1), 'LEFT'),
+            ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
+            ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
+            ('FONTSIZE', (0,0), (-1,-1), 8),
+            ('BOTTOMPADDING', (0,0), (-1,0), 6),
+            ('TOPPADDING', (0,0), (-1,0), 6),
+            ('BACKGROUND', (0,1), (-1,-1), colors.HexColor('#F5F6FA')),
+            ('GRID', (0,0), (-1,-1), 0.4, colors.HexColor('#DDE4EB')),
+            ('LEFTPADDING', (1,3), (1,3), 10),
+            ('WORDWRAP', (1,3), (1,3), 'CJK'),
+        ]))
+        story.append(table)
+        story.append(Spacer(1, 0.3*inch))
+        story.append(Paragraph("Prepared by EvalBot - AI-Powered HR Analysis", body_text))
+        story.append(PageBreak())
+
+        # Detailed Analysis
+        story.append(Paragraph("Detailed Candidate Evaluation", h1))
+
+        # Communication and Vocal Dynamics
+        story.append(Paragraph("1. Communication & Vocal Dynamics", h2))
+        voice_analysis = analysis_data.get('voice_analysis', {})
+        if voice_analysis and 'error' not in voice_analysis:
             table_data = [
-                ['Metric', 'Value'],
-                ['Interview Duration', f"{analysis_data['text_analysis']['total_duration']:.2f} seconds"],
-                ['Speaker Turns', f"{analysis_data['text_analysis']['speaker_turns']}"],
-                ['Participants', participants_str],
+                ['Metric', 'Value', 'HR Insight'],
+                ['Speaking Rate', f"{voice_analysis.get('speaking_rate', 0):.2f} words/sec", 'Benchmark: 2.0-3.0 wps; impacts clarity'],
+                ['Filler Words', f"{voice_analysis.get('filler_ratio', 0) * 100:.1f}%", 'High usage reduces credibility'],
+                ['Anxiety', voice_analysis.get('interpretation', {}).get('anxiety_level', 'N/A'), f"Score: {voice_analysis.get('composite_scores', {}).get('anxiety', 0):.3f}"],
+                ['Confidence', voice_analysis.get('interpretation', {}).get('confidence_level', 'N/A'), f"Score: {voice_analysis.get('composite_scores', {}).get('confidence', 0):.3f}"],
+                ['Fluency', voice_analysis.get('interpretation', {}).get('fluency_level', 'N/A'), 'Drives engagement'],
             ]
-            table = Table(table_data, colWidths=[2.0*inch, 4.0*inch])
+            table = Table(table_data, colWidths=[1.5*inch, 1.3*inch, 3.2*inch])
             table.setStyle(TableStyle([
-                ('Background', (0,0), (-1,0), colors.HexColor('#0050BC')),
+                ('BACKGROUND', (0,0), (-1,0), colors.HexColor('#0050BC')),
                 ('TEXTCOLOR', (0,0), (-1,0), colors.white),
                 ('ALIGN', (0,0), (-1,-1), 'LEFT'),
                 ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
                 ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
                 ('FONTSIZE', (0,0), (-1,-1), 8),
-                ('BOTTOMPADING', (0,0), (-1,0), 6),
-                ('TOPPADING', (0,0), (-1,0), 6),
-                ('Background', (0,1), (-1,-1), colors.HexColor('#F5F6FA')),
+                ('BOTTOMPADDING', (0,0), (-1,0), 6),
+                ('TOPPADDING', (0,0), (-1,0), 6),
+                ('BACKGROUND', (0,1), (-1,-1), colors.HexColor('#F5F6FA')),
                 ('GRID', (0,0), (-1,-1), 0.4, colors.HexColor('#DDE4EB')),
-                ('LEFTPAD', (1,3), (1,3), 10),
-                ('WORDWRAP', (1,3), (1,3), 'CJK'),
             ]))
             story.append(table)
-            story.append(Spacer(1, 0.3*inch))
-            story.append(Paragraph("Prepared by EvalBot - AI-Powered HR Analysis", body_text))
-            story.append(PageBreak())
-
-            # Detailed Analysis
-            story.append(Paragraph("Detailed Candidate Evaluation", h1))
-
-            # Communication and Vocal Dynamics
-            story.append(Paragraph("1. Communication & Vocal Dynamics", h2))
-            voice_analysis = analysis_data.get('voice_analysis', {})
-            if voice_analysis and 'error' not in voice_analysis:
-                table_data = [
-                    ['Metric', 'Value', 'HR Insight'],
-                    ['Speaking Rate', f"{voice_analysis.get('speaking_rate', 0):.2f} words/sec", 'Benchmark: 2.0-3.0 wps; impacts clarity'],
-                    ['Filler Words', f"{voice_analysis.get('filler_ratio', 0) * 100:.1f}%", 'High usage reduces credibility'],
-                    ['Anxiety', voice_analysis.get('interpretation', {}).get('anxiety_level', 'N/A'), f"Score: {voice_analysis.get('composite_scores'), {}).get('anxiety', 0):.3f}"],
-                    ['Confidence', voice_analysis.get('('interpretation', {}).get('confidence_level'), 'N/A'), f"Score: {voice_analysis.get('('composite_scores', {}).get('confidence', 0):.3f}"],
-                    ['Fluency', voice_analysis.get('interpretation', {}).get('fluency_level', 'N/A'), 'Drives engagement'),
-                ]
-                table = Table(table_data, colWidths=[1.5*inch, 1.3*inch, 3.2*inch])
-                table.setStyle(TableStyle([
-                    ('Background', (0,0), (-1,0), colors.HexColor('#0050BC')),
-                    ('TEXTCOLOR', (0,0), (-1,0), colors.white),
-                    ('ALIGN', (0,0), (-1,-1), 'LEFT'),
-                    ('VALIGN', (0,0), (-1,-1), 'MIDDLE'),
-                    ('FONTNAME', (0,0), (-1,0), 'Helvetica-Bold'),
-                    ('FONTSIZE', (0,0), (-1,-1), 8),
-                    ('BOTTOMPADING', (0,0), (-1,0), 6),
-                    ('TOPPADING', (0,0), (-1,0), 6),
-                    ('Background', (0,1), (-1,-1), colors.HexColor('#F5F6FA')),
-                    ('GRID', (0,0), (-1,-1), 0.4, colors.HexColor('#DDE4EB')),
-                ]))
-            story.append(table)
             story.append(Spacer(1, 0.15*inch))
             chart_buffer = io.BytesIO()
             generate_anxiety_confidence_chart(voice_analysis.get('composite_scores', {}), chart_buffer)
@@ -898,7 +898,7 @@ def create_company_pdf_report(analysis_data: Dict, output_path: str, gemini_repo
                 if 'Executive Summary' in section_title:
                     current_section = 'Executive Summary'
                     current_subsection = None
-                elif section_title == 'Communication and Vocal Dynamics':
+                elif 'Communication' in section_title:
                     current_section = 'Communication'
                     current_subsection = None
                 elif 'Competency' in section_title:
@@ -907,7 +907,7 @@ def create_company_pdf_report(analysis_data: Dict, output_path: str, gemini_repo
                 elif 'Role Fit' in section_title:
                     current_section = 'Role Fit'
                     current_subsection = None
-                elif section_title == 'Recommendations':
+                elif 'Recommendations' in section_title:
                     current_section = 'Recommendations'
                     current_subsection = None
                 logger.debug(f"Set section: {current_section}")
@@ -916,14 +916,14 @@ def create_company_pdf_report(analysis_data: Dict, output_path: str, gemini_repo
                 if not clean_line:
                     continue
                 clean_line = re.sub(r'[^\w\s.,;:-]', '', clean_line)
-                logger.debug(f"Processing bullet: {clean_line}, section: {current_section}, {subsection: current_subsection}")
+                logger.debug(f"Processing bullet: {clean_line}, section: {current_section}, subsection: {current_subsection}")
                 if current_section in ['Competency', 'Recommendations']:
                     if current_subsection is None:
                         if current_section == 'Competency':
                             current_subsection = 'Strengths'
                         elif current_section == 'Recommendations':
                             current_subsection = 'Development'
-                        logger.debug(f"Default subsetion set to: {current_subsection}")
+                        logger.debug(f"Default subsection set to: {current_subsection}")
                     if current_subsection:
                         sections[current_section][current_subsection].append(clean_line)
                     else:
@@ -939,63 +939,63 @@ def create_company_pdf_report(analysis_data: Dict, output_path: str, gemini_repo
                     else:
                         current_subsection = 'Strengths' if current_section == 'Competency' else 'Development'
                         sections[current_section][current_subsection].append(clean_line)
-                        logger.debug(f"Default subsetion for non-bullet set to: {current_subsection}")
+                        logger.debug(f"Default subsection for non-bullet set to: {current_subsection}")
                 else:
                     sections[current_section].append(clean_line)
 
-            # Executive Summary
-            story.append(Paragraph("2. Executive Summary", h2))
-            if sections['Executive Summary']:
-                for line in sections['Executive Summary']:
-                    story.append(Paragraph(line, bullet_style))
-            else:
-                story.append(Paragraph("Candidate showed moderate engagement; further assessment needed.", bullet_style))
-                story.append(Paragraph(f"Interview lasted {analysis_data['text_analysis']['total_duration']:.2f} seconds with {analysis_data['text_analysis']['speaker_turns']} turns.", bullet_style))
-            story.append(Spacer(1, 0.15*inch))
+        # Executive Summary
+        story.append(Paragraph("2. Executive Summary", h2))
+        if sections['Executive Summary']:
+            for line in sections['Executive Summary']:
+                story.append(Paragraph(line, bullet_style))
+        else:
+            story.append(Paragraph("Candidate showed moderate engagement; further assessment needed.", bullet_style))
+            story.append(Paragraph(f"Interview lasted {analysis_data['text_analysis']['total_duration']:.2f} seconds with {analysis_data['text_analysis']['speaker_turns']} turns.", bullet_style))
+        story.append(Spacer(1, 0.15*inch))
 
-            # Competency and Content
-            story.append(Paragraph("3. Competency & Content", h2))
-            story.append(Paragraph("Strengths", h3))
-            if sections['Competency']['Strengths']:
-                for line in sections['Competency']['Strengths']:
-                    story.append(Paragraph(line, bullet_style))
-            else:
-                story.append(Paragraph("Strengths not fully assessed; candidate demonstrated consistent communication.", bullet_style))
-            story.append(Spacer(1, 0.1*inch))
-            story.append(Paragraph("Growth Areas", h3))
-            if sections['Competency']['Growth Areas']:
-                for line in sections['Competency']['Growth Areas']:
-                    story.append(Paragraph(line, bullet_style))
-            else:
-                story.append(Paragraph("Consider enhancing specificity in responses to highlight expertise.", bullet_style))
-            story.append(Spacer(1, 0.15*inch))
+        # Competency and Content
+        story.append(Paragraph("3. Competency & Content", h2))
+        story.append(Paragraph("Strengths", h3))
+        if sections['Competency']['Strengths']:
+            for line in sections['Competency']['Strengths']:
+                story.append(Paragraph(line, bullet_style))
+        else:
+            story.append(Paragraph("Strengths not fully assessed; candidate demonstrated consistent communication.", bullet_style))
+        story.append(Spacer(1, 0.1*inch))
+        story.append(Paragraph("Growth Areas", h3))
+        if sections['Competency']['Growth Areas']:
+            for line in sections['Competency']['Growth Areas']:
+                story.append(Paragraph(line, bullet_style))
+        else:
+            story.append(Paragraph("Consider enhancing specificity in responses to highlight expertise.", bullet_style))
+        story.append(Spacer(1, 0.15*inch))
 
-            # Role Fit
-            story.append(Paragraph("4. Role Fit & Potential", h2))
-            if sections['Role Fit']:
-                for line in sections['Role Fit']:
-                    story.append(Paragraph(line, bullet_style))
-            else:
-                story.append(Paragraph("Potential for role fit exists; further evaluation needed to confirm alignment.", bullet_style))
-            story.append(Spacer(1, 0.15*inch))
+        # Role Fit
+        story.append(Paragraph("4. Role Fit & Potential", h2))
+        if sections['Role Fit']:
+            for line in sections['Role Fit']:
+                story.append(Paragraph(line, bullet_style))
+        else:
+            story.append(Paragraph("Potential for role fit exists; further evaluation needed to confirm alignment.", bullet_style))
+        story.append(Spacer(1, 0.15*inch))
 
-            # Recommendations
-            story.append(Paragraph("5. Recommendations", h2))
-            story.append(Paragraph("Development Priorities", h3))
-            if sections['Recommendations']['Development']:
-                for line in sections['Recommendations']['Development']:
-                    story.append(Paragraph(line, bullet_style))
-            else:
-                story.append(Paragraph("Enrollment in communication training to reduce filler words.", bullet_style))
-            story.append(Spacer(1, 0.1*inch))
-            story.append(Paragraph("Next Steps for Hiring Managers", h3))
-            if sections['Recommendations']['Next Steps']:
-                for line in sections['Recommendations']['Next Steps']:
-                    story.append(Paragraph(line, bullet_style))
-            else:
-                story.append(Paragraph("Schedule a technical assessment to evaluate role-specific skills.", bullet_style))
-            story.append(Spacer(1, 0.15*inch))
-            story.append(Paragraph("This report provides actionable insights to support hiring decisions.", body_text))
+        # Recommendations
+        story.append(Paragraph("5. Recommendations", h2))
+        story.append(Paragraph("Development Priorities", h3))
+        if sections['Recommendations']['Development']:
+            for line in sections['Recommendations']['Development']:
+                story.append(Paragraph(line, bullet_style))
+        else:
+            story.append(Paragraph("Enrollment in communication training to reduce filler words.", bullet_style))
+        story.append(Spacer(1, 0.1*inch))
+        story.append(Paragraph("Next Steps for Hiring Managers", h3))
+        if sections['Recommendations']['Next Steps']:
+            for line in sections['Recommendations']['Next Steps']:
+                story.append(Paragraph(line, bullet_style))
+        else:
+            story.append(Paragraph("Schedule a technical assessment to evaluate role-specific skills.", bullet_style))
+        story.append(Spacer(1, 0.15*inch))
+        story.append(Paragraph("This report provides actionable insights to support hiring decisions.", body_text))
 
         doc.build(story, onFirstPage=header_footer, onLaterPages=header_footer)
         logger.info(f"Company PDF report successfully generated at {output_path}")